用于从人体研究中获取的多通道超极化 C 成像数据的线圈组合方法。
Coil combination methods for multi-channel hyperpolarized C imaging data from human studies.
机构信息
Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States; UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, CA, United States.
Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States; UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, CA, United States.
出版信息
J Magn Reson. 2019 Apr;301:73-79. doi: 10.1016/j.jmr.2019.01.015. Epub 2019 Feb 1.
Effective coil combination methods for human hyperpolarized C spectroscopy multi-channel data had been relatively unexplored. This study implemented and tested several coil combination methods, including (1) the sum-of-squares (SOS), (2) singular value decomposition (SVD), (3) Roemer method by using reference peak area as a sensitivity map (RefPeak), and (4) Roemer method by using ESPIRiT-derived sensitivity map (ESPIRiT). These methods were evaluated by numerical simulation, thermal phantom experiments, and human cancer patient studies. Overall, the SVD, RefPeak, and ESPIRiT methods demonstrated better accuracy and robustness than the SOS method. Extracting complex pyruvate signal provides an easy and excellent approximation of the coil sensitivity map while maintaining valuable phase information of the coil-combined data.
针对人体高极化 C 波谱多通道数据的有效线圈组合方法尚未得到充分研究。本研究实施并测试了几种线圈组合方法，包括（1）均方和（SOS），（2）奇异值分解（SVD），（3）使用参考峰面积作为灵敏度图的 Roemer 方法（RefPeak），以及（4）使用 ESPIRiT 衍生灵敏度图的 Roemer 方法（ESPIRiT）。这些方法通过数值模拟、热体模实验和人体癌症患者研究进行了评估。总体而言，SVD、RefPeak 和 ESPIRiT 方法比 SOS 方法具有更好的准确性和鲁棒性。提取复杂的丙酮酸信号在保持线圈组合数据有价值的相位信息的同时，提供了对线圈灵敏度图的简单而出色的逼近。
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